Existing methods which use light to characterize materials generally employ classical spectrophotometric methods. In these methods a spectrally narrow band beam is used together with detectors to quantify the transmission, absorption or reflection of the material. Such a narrow band beam conventionally has a continuously variable wavelength derived by monochromatizing a broadband source. This system functions well, provided that before and after interacting with the material, the transmitted or reflected detection energy is predominantly in the form of a beam. Materials with a high degree of scattering (e.g. biological tissue, colloids, precipitates, polymers) are difficult to accurately quantify in this manner, however, because the radiation loses its directionality after interacting with the material. When a priori predictability of the output radiation pattern is not highly correlated to its input direction, such material will be called turbid in the discussion that follows. Optical dispersion also occurs by angular refractive variations on sample surfaces and is another effect that produces scattering. In these cases, data obtained by conventional methods generally depend highly upon the geometric arrangement. Stability is often poor with low signal to noise ratios because a good deal of the fundamental spectral radiance (photons per sec/cm.sup.2 /steradian/nm) from the source is wasted in creating a directional beam of which only a small portion is recoverable after interaction. Substantial data processing methods are needed for geometric analysis, noise reduction and stability enhancement.
Spectroradiometers and photometers are most accurate for non-scattering materials. With turbid materials the precise topologic configuration greatly affects the radiation received by a detector. The further the detector is from each point of scattering the more measurement accuracy depends upon geometry. Also, slightly translucent materials having thick dimensions have negligible optical transmission and/or have rough surfaces which scatter light thus preventing accurate measurement of bulk properties. Conventional spectrometers that measure spectral interactions using directional beams poorly accommodate spatial scattering properties of materials.
In the last twenty years techniques have emerged in which the applied wavelengths are not composed of a single spectral peak which can be varied continuously. Instead spectral components can be measured in groups. One such method is known as Hadamard transform spectroscopy and the emitted spectral components are combined in groups based on Hadamard matrices. Such spectral groups are generally applied simultaneously as a beam of radiation and geometric difficulties introduced by scattering are still present. The advantage is that the noise per frequency component can be reduced. The same technique can be applied to images.
A natural system which operates on the global structure of intensities at various frequencies is the eye which has evolved over many millions of years. Animals often receive indefinite visual information from their environment yet some have the ability to perceive very small differences in color. These abilities often exceed the capability of artificial systems so that in the past twenty or so years computer vision workers have turned to study possible analogs in the animal world with the hope of emulating successes of nature. The human visual system has four types of color receptors, the tristimulus red, green, and blue (RGB) cones, and the rods. Yet it is able to distinguish between millions of different colors even when background illumination varies greatly. Spectral aspects of the tristimulus part of this analog to nature has been referenced in U.S. Pat. No. 5,434,412 to Sodickson et al. However, human diversity in color perception, acuity, and ability to recognize through neural data analysis derives in great part from spatial as well as spectral characterization of the retinal image via about 180 million photoreceptors of each eye. Interaction of spectral and spatial photoreception is exemplified by many optical illusions where color changes cause spatial variations and vice versa. The interdependence of spatial and spectral information becomes increasingly significant in materials with increased turbidity. It is also important to recognize that, as a material identifier, color is more than the appearance to the eye in RGB. The identification "colors" of objects extend spectroradiometrically beyond the visible spectrum to all wavelengths. For many materials the most potent optical discrimination properties occur in the infrared region and are invisible to the human eye.
For reasons discussed above, spectroscopic examination of materials for biological analysis, tissue studies, machine vision, industrial control, environmental monitoring, etc. are often hampered by geometric effects of scattering over a broad spectral range. Moreover, spectral density variables employed to analyze materials are often inappropriately applied. Significance of the density of states of the material under analysis, relative to the impinging radiation is often overlooked, as was pointed out by Wunderman in "A clarification of spectral characterization units for quantum detectors and emitters", Applied Optics, January 1968.